Agent

Configures an Agno AI agent with all its dependencies — model, tools, knowledge base, memory, and storage.

Config

Field	Type	Required	Default	Description
`name`	`string`	No	Resource name	Display name for the agent
`description`	`string`	No	—	Agent description
`role`	`string`	No	—	Agent role description
`model`	`Dependency`	Yes	—	Reference to `agno/models/anthropic` or `agno/models/openai`
`instructions`	`list[string]`	No	—	System instructions for the agent
`prompt`	`Dependency`	No	—	Reference to `agno/prompt`; its rendered text replaces `instructions`
`tools`	`list[Dependency]`	No	`[]`	References to `agno/tools/mcp` or `agno/tools/websearch`
`knowledge`	`Dependency`	No	—	Reference to `agno/knowledge`
`db`	`Dependency`	No	—	Reference to `agno/db/postgres` for session storage
`memory`	`Dependency`	No	—	Reference to `agno/memory/manager`
`output_schema`	`object`	No	—	JSON schema for structured responses. The top-level `type` must be `object`. Without it, the agent returns plain text
`markdown`	`boolean`	No	`false`	Format responses as Markdown
`add_datetime_to_context`	`boolean`	No	`false`	Include current datetime in context
`read_chat_history`	`boolean`	No	Auto	Read chat history from DB (auto-enabled when `db` is set)
`add_history_to_context`	`boolean`	No	Auto	Add history to context (auto-enabled when `db` is set)
`num_history_runs`	`integer`	No	—	Number of previous runs to include in history
`enable_agentic_memory`	`boolean`	No	`false`	Enable agentic memory capabilities
`update_memory_on_run`	`boolean`	No	`false`	Update memory after each run
`add_memories_to_context`	`boolean`	No	—	Add stored memories to context
`enable_session_summaries`	`boolean`	No	`false`	Enable session summary generation

Outputs

Field	Type	Description
`spec`	`object`	Serialized agent specification for runtime reconstruction
`pip_dependencies`	`list[string]`	Python packages required by agent tools and knowledge

Dependencies

Depends on:

agno/models/anthropic or agno/models/openai (required) — the LLM powering the agent
agno/tools/mcp or agno/tools/websearch (optional) — tool integrations
agno/knowledge (optional) — semantic search knowledge base
agno/memory/manager (optional) — persistent memory
agno/db/postgres (optional) — session and chat history storage
agno/prompt (optional) — reusable prompt template

Depended on by:

agno/team — as a team member
agno/runner — for deployment to Kubernetes

Example

provider: agno
resource: agent
name: my-assistant
config:
  description: "A helpful AI assistant"
  model:
    provider: agno
    resource: models/anthropic
    name: claude
  instructions:
    - "You are a helpful assistant."
    - "Always respond concisely."
  tools:
    - provider: agno
      resource: tools/websearch
      name: search
  markdown: true

Notes

The agent resource is stateless — it produces a serializable spec used by agno/runner for deployment.
When db is set, read_chat_history and add_history_to_context are automatically enabled unless explicitly overridden.
Updating a dependency (e.g., changing the model) triggers the agent to rebuild automatically.

Getting Started

Concepts

Resource Catalog

Agno (AI Agents)

GCP

Kubernetes

Building Providers

Config

Outputs

Dependencies

Example

Notes

​Config

​Outputs

​Dependencies

​Example

​Notes

Config

Outputs

Dependencies

Example

Notes